Cipher Type Detection
Malte Nuhn, Kevin K. Knight · 2014
Manual analysis and decryption of enciphered documents is a tedious and error prone work.Often-even after spending large amounts of time on a particular cipher-no decipherment can be found.Automating the decryption of various types of ciphers makes it possible to sift through the large number of encrypted messages found in libraries and archives, and to focus human effort only on a small but potentially interesting subset of them.In this work, we train a classifier that is able to predict which encipherment method has been used to generate a given ciphertext.We are able to distinguish 50 different cipher types (specified by the American Cryptogram Association) with an accuracy of 58.5%.This is a 11.2% absolute improvement over the best previously published classifier.